Predicting the Influence of Multi-Scale Spatial Autocorrelation on Soil-Landform Modeling

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00027073%3A_____%2F16%3AN0000044" target="_blank" >RIV/00027073:_____/16:N0000044 - isvavai.cz</a>

Result on the web

<a href="https://dl.sciencesocieties.org/publications/sssaj/abstracts/80/2/409?access=0&view=pdf" target="_blank" >https://dl.sciencesocieties.org/publications/sssaj/abstracts/80/2/409?access=0&view=pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.2136/sssaj2015.10.0370" target="_blank" >10.2136/sssaj2015.10.0370</a>

Result language

angličtina

Original language name

Predicting the Influence of Multi-Scale Spatial Autocorrelation on Soil-Landform Modeling

Original language description

Although numerous soil–landform modeling investigations have documented the effects and importance of spatial autocorrelation (SAC), little is known about how to predict the magnitude of those effects from the degree of SAC in the model variables. In this study, we quantified the SAC inherent in soil and landform variables of four widely divergent pedogeomorphological systems around the world to examine general relationships between SAC and spatial regression model results. Spatial regressions were performed by incorporating spatial filters, extracted by spatial eigenvector mapping, into non-spatial models as additional predictor variables. Results indicated that incorporation of spatial filters improved the performance of the non-spatial regressions—increases in R2 and decreases in both Akaike Information Criterion (AIC) and residual SAC were observed. More remarkable was that the degree of improvement was strongly and linearly related (i.e., proportional) to the level of SAC inherently possessed by each soil variable. Our findings show that spatial modeling outcomes are sensitive to the degree of SAC possessed by a soil property when treated as a response variable. Thus, the level of SAC present in a soil variable can serve as a direct indicator for how much improvement a non-spatial model will undergo if that SAC is appropriately taken into account.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

DF - Pedology

OECD FORD branch

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Project

<a href="/en/project/LH12039" target="_blank" >LH12039: Role of disturbance in soil formation and soil variability in temperate forests: synthesis through soil-formation-processes, spatial and time scales</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2016

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Soil Science Society of America Journal

ISSN

0361-5995

e-ISSN

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Volume of the periodical

80

Issue of the periodical within the volume

2

Country of publishing house

US - UNITED STATES

Number of pages

11

Pages from-to

409-419

UT code for WoS article

000376399200014

EID of the result in the Scopus database

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